Instructions to use akshan-main/modular-sdxl-upscale with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use akshan-main/modular-sdxl-upscale with Diffusers:
pip install -U diffusers transformers accelerate
from diffusers import ControlNetModel, StableDiffusionControlNetPipeline controlnet = ControlNetModel.from_pretrained("akshan-main/modular-sdxl-upscale") pipe = StableDiffusionControlNetPipeline.from_pretrained( "fill-in-base-model", controlnet=controlnet ) - Notebooks
- Google Colab
- Kaggle
| { | |
| "_blocks_class_name": "MultiDiffusionUpscaleBlocks", | |
| "_class_name": "StableDiffusionXLModularPipeline", | |
| "_diffusers_version": "0.38.0.dev0", | |
| "controlnet": [ | |
| null, | |
| null, | |
| { | |
| "pretrained_model_name_or_path": null, | |
| "subfolder": "", | |
| "type_hint": [ | |
| "diffusers", | |
| "ControlNetModel" | |
| ] | |
| } | |
| ], | |
| "force_zeros_for_empty_prompt": true, | |
| "requires_aesthetics_score": false, | |
| "scheduler": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "scheduler", | |
| "type_hint": [ | |
| "diffusers", | |
| "EulerDiscreteScheduler" | |
| ] | |
| } | |
| ], | |
| "text_encoder": [ | |
| "transformers", | |
| "CLIPTextModel", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "text_encoder", | |
| "type_hint": [ | |
| "transformers", | |
| "CLIPTextModel" | |
| ] | |
| } | |
| ], | |
| "text_encoder_2": [ | |
| "transformers", | |
| "CLIPTextModelWithProjection", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "text_encoder_2", | |
| "type_hint": [ | |
| "transformers", | |
| "CLIPTextModelWithProjection" | |
| ] | |
| } | |
| ], | |
| "tokenizer": [ | |
| "transformers", | |
| "CLIPTokenizer", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "tokenizer", | |
| "type_hint": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ] | |
| } | |
| ], | |
| "tokenizer_2": [ | |
| "transformers", | |
| "CLIPTokenizer", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "tokenizer_2", | |
| "type_hint": [ | |
| "transformers", | |
| "CLIPTokenizer" | |
| ] | |
| } | |
| ], | |
| "unet": [ | |
| "diffusers", | |
| "UNet2DConditionModel", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "unet", | |
| "type_hint": [ | |
| "diffusers", | |
| "UNet2DConditionModel" | |
| ] | |
| } | |
| ], | |
| "vae": [ | |
| "diffusers", | |
| "AutoencoderKL", | |
| { | |
| "pretrained_model_name_or_path": "stabilityai/stable-diffusion-xl-base-1.0", | |
| "subfolder": "vae", | |
| "type_hint": [ | |
| "diffusers", | |
| "AutoencoderKL" | |
| ] | |
| } | |
| ] | |
| } |